Micro Aerial Vehicles (MAVs) are increasingly used for industrial inspection, surveillance, and emergency response tasks, but traditional coverage path planning techniques often struggle with energy efficiency and computational constraints in multi-robot scenarios. We propose a novel multi-robot coverage path planning approach that uses a PH-tree data structure for real-time identification of unobserved regions. That leads to online task assignment without the computational burden of tracking frontiers or performing Next Best View (NBV) calculations. Our method was checked against top-notch state-of-the-art frontier-based techniques and those of NBV. Each technique was adapted to work under the same conditions to provide a comparison on a similar basis, working with the known geometry of the environment.